News

Our paper on "Emotions in Context" accepted at CVPR 2017

We present a database for studying how to model context to understand people emotional states. We show promising results at estimating 26 affective categories and continuous dimensions (pdf, Project Page)

Our work on "Class Activation Map" accepted at CVPR 2016

We revisit the global average pooling layer and shed light on how it explicitly enables the convolutional neural network to have remarkable localization ability despite being trained on image-level labels (Project Page).